Regular:

We consider the problem of detecting a target signature which is known (up to an amplitude factor) to belong to a (possibly very) large library of signatures. Thus we know how each signature to be... View More

We consider the problem of detecting a target signature which is known (up to an amplitude factor) to belong to a (possibly very) large library of signatures. Thus we know how each signature to be detected looks like, but we do not know which one is activated under H1. We propose a minimax approach for this problem aimed at maximizing the worst detection performance. Optimization issues and connections with One-Class classifiers are discussed and illustrated geometrically. Numerical results comparing the proposed approach to the classical sparse-coding dictionary learning technique K-SVD are provided on astrophysical hyperspectral data.

1.1 This guide lists and discusses features of a spectrometer or polychromator used for optical emission, direct-reading, spectrochemical analysis. A polychromator in this sense consists of a spectrometer with an extended and fixed wavelength range and an array of fixed exit slits to isolate the ...

A robust model predictive control algorithm for discrete linear systems with both state and input delays subjected to constrained input control is presented, where the polytopic uncertainties exist in both state matrices and input matrices. The algorithm optimizes an upper bound with respect to a st...

Powerful expressive ability of semantic information, to be easily computed and flexibility are basic features of digital product model (DPM). Using ontology and object-oriented principle (OOP) together to cope with problems in modeling is brought forward in this paper. The two are widely used and do...